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NEW QUESTION: 1
スクラムチームの最適なサイズは次のとおりです。
A. 3〜9
B. 0
C. 1
D. 状況による
Answer: A

NEW QUESTION: 2
Which configuration allows users to reach YouTube from a local Internet breakout?
A)

B)

C)

D)

A. Option A
B. Option D
C. Option C
D. Option B
Answer: D

NEW QUESTION: 3
ゲーム会社は、レイヤー4のユーザーと通信するマルチプレーヤーゲームの単一のアベイラビリティーゾーンに複数のAmazon EC2インスタンスを持っています。最高技術責任者（CTO）は、アーキテクチャの可用性と費用対効果を高くしたいと考えています。
これらの要件を満たすために、ソリューションアーキテクトは何をすべきですか？ （2つ選択してください。）
A. EC2インスタンスの数を増やします。
B. 複数のアベイラビリティーゾーンでインスタンスを自動的に追加または削除するようにAuto Scalingグループを構成します。
C. EC2インスタンスの前にネットワークロードバランサーを設定します。
D. EC2インスタンスの前にApplication Load Balancerを設定します
E. EC2インスタンスの数を減らす
Answer: B,C
Explanation:
Explanation
Network Load Balancer overview
A Network Load Balancer functions at the fourth layer of the Open Systems Interconnection (OSI) model. It can handle millions of requests per second. After the load balancer receives a connection request, it selects a target from the target group for the default rule. It attempts to open a TCP connection to the selected target on the port specified in the listener configuration.
When you enable an Availability Zone for the load balancer, Elastic Load Balancing creates a load balancer node in the Availability Zone. By default, each load balancer node distributes traffic across the registered targets in its Availability Zone only. If you enable cross-zone load balancing, each load balancer node distributes traffic across the registered targets in all enabled Availability Zones. For more information, see Availability Zones.
If you enable multiple Availability Zones for your load balancer and ensure that each target group has at least one target in each enabled Availability Zone, this increases the fault tolerance of your applications. For example, if one or more target groups does not have a healthy target in an Availability Zone, we remove the IP address for the corresponding subnet from DNS, but the load balancer nodes in the other Availability Zones are still available to route traffic. If a client doesn't honor the time-to-live (TTL) and sends requests to the IP address after it is removed from DNS, the requests fail.
For TCP traffic, the load balancer selects a target using a flow hash algorithm based on the protocol, source IP address, source port, destination IP address, destination port, and TCP sequence number. The TCP connections from a client have different source ports and sequence numbers, and can be routed to different targets. Each individual TCP connection is routed to a single target for the life of the connection.
For UDP traffic, the load balancer selects a target using a flow hash algorithm based on the protocol, source IP address, source port, destination IP address, and destination port. A UDP flow has the same source and destination, so it is consistently routed to a single target throughout its lifetime. Different UDP flows have different source IP addresses and ports, so they can be routed to different targets.
An Auto Scaling group contains a collection of Amazon EC2 instances that are treated as a logical grouping for the purposes of automatic scaling and management. An Auto Scaling group also enables you to use Amazon EC2 Auto Scaling features such as health check replacements and scaling policies. Both maintaining the number of instances in an Auto Scaling group and automatic scaling are the core functionality of the Amazon EC2 Auto Scaling service.
The size of an Auto Scaling group depends on the number of instances that you set as the desired capacity.
You can adjust its size to meet demand, either manually or by using automatic scaling.
An Auto Scaling group starts by launching enough instances to meet its desired capacity. It maintains this number of instances by performing periodic health checks on the instances in the group. The Auto Scaling group continues to maintain a fixed number of instances even if an instance becomes unhealthy. If an instance becomes unhealthy, the group terminates the unhealthy instance and launches another instance to replace it.
https://docs.aws.amazon.com/elasticloadbalancing/latest/network/introduction.html
https://docs.aws.amazon.com/autoscaling/ec2/userguide/AutoScalingGroup.html

NEW QUESTION: 4
A company maintains an application responsible for processing several thousand external callbacks each day. The company's System administrators want to know how many callbacks are being received on a rolling basis, and they want this data available for 10 days. The company also wants the ability to issue automated alerts if the number of callbacks exceeds the defined thresholds.
What is the MOST cost-effective way to address the need to track and alert on these statistics?
A. Push callback data to Amazon CloudWatch as a custom metric and use the CloudWatch alerting mechanisms to alert System Administrators.
B. Push callback data to Amazon Kinesis Data Streams and invoke an AWS Lambda function that stores data in Amazon DynamoDB and sends the required alerts.
C. Push callback data to an Amazon RDS database that can be queried to show historical data and to alert on exceeded thresholds.
D. Push callback data to AWS X-Ray and use AWS Lambda to query, display, and alert on exceeded thresholds.
Answer: A